Fault detection and location based SVM for three phase transmission lines utilizing positive sequence fault components
DOI:
https://doi.org/10.15649/2346030X.3302Keywords:
Fault identification, Fault classification, Support Vector Machine (SVM), Positive Sequence Analyzer, Transmission lines, Electrical fault detectionAbstract
Transmission lines are an imperative element of the modern power systems. Any faults in them can cause an undesirable interruption in power supply. Precise analysis of these faults is important in-order to ensure an incessant supply of power. For this purpose, fault detection and classification are needed to clear any such faults and re-establish the system to maintain its normal operation. In this paper, a novel integrated approach of protective relaying with enhanced support vector machine algorithm has been adopted for detecting faults and its location estimation in long transmission line. The proposed scheme is successfully able to detect and classify different symmetrical and unsymmetrical faults along with some peculiar cases related to High Impedance Faults (HIF) and evolving faults, current transformer (CT) saturation/ capacitive voltage transformer (CVT) transient, close-in faults, swing condition, source strength variation, etc. The comparative analysis with recent proposed techniques declared the potentiality and robustness of the scheme
References
T. Bouthiba, ‘‘Fault location in Ehv transmission lines using artificial neural networks,’’ Int. J. Appl. Math. Comput. Sci., vol. 14, no. 1, pp. 69–78, 2004, Accessed: Sep. 26, 2022. [Online]. Available: https://eudml.org/doc/207681#.YzITSHTKOAk.mendeley
M. Mirzaei, M. Z. A. A. Kadir, E. Moazami, and H. Hizam, ‘‘Review of fault location methods for distribution power system,’’ Austral. J. Basic Appl. Sci., vol. 3, no. 3, pp. 2670–2676, 2009.
A. Jain, A. S. Thoke, and R. N. Patel, ‘‘Double circuit transmission line fault distance location using artificial neural network,’’ in Proc. World Congr. Nature Biologically Inspired Comput. (NaBIC), 2009, pp. 13–18, doi: 10.1109/NABIC.2009.5393593.
Q. Huang, W. Zhen, and P. W. T. Pong, ‘‘A novel approach for fault location of overhead transmission line with noncontact magnetic-field measurement,’’ IEEE Trans. Power Del., vol. 27, no. 3, pp. 1186–1195, Jul. 2012, doi: 10.1109/TPWRD.2012.2190427.
A. S. Ghoniem, ‘‘Sub-line transient magnetic fields calculation approach for fault detection, classification and location of high voltage transmission line,’’ Int. J. Electr. Eng. Informat., vol. 11, no. 3, pp. 548–563, Sep. 2019, doi: 10.15676/ijeei.2019.11.3.7
Dalstein T, Kluicke B. Neural network approach to fault classification for high speed protection relaying. IEEE Trans, P&D 1995;10 (2):1002–11.
Dash PK, Pradhan AK, Panda G. a novel fuzzy neural network based distance relaying scheme. IEEE T Power Deliver 2000;15 (3):902–7.
Wang H, Keeerthipala WW. Fuzzy neuro approach to fault classification for transmission line protection. IEEE T Power Deliver 1998;13 (4):1093–102.
Aggarwal RK, Xuan QY, Dunn RW, Johns AT, Bennett A. A novel fault classification technique for double-circuit lines based on a combined unsupervised/supervised neural network. IEEE Trans Power Delivery 1999;14(4):1250–6.
Makwana VH, Bhalja B. New adaptive digital distance relaying scheme for double infeed parallel transmission line during inter-circuit faults. IET Gener Transm Distrib 2011;5:667–73.
Coury DV, Oleskovicz M, Aggarwal RK. ANN routine for fault detection, classification and location in Transmission lines. Electric Power Compo Syst 2002;30:1137–49.
Dash PK, Samantaray SR, Panda G. Fault classification and section identification of an advanced series-compensated transmission line using support vector machine. IEEE Trans Power Delivery 2007;22(1) [January].
Samantaray SR, Dash PK, Panda G. Distance relaying for transmission line using support vector machine and radial basis function neural network. Int J Electr Power Energy Syst 2007;29:551–6.
Ravikumar B, Thukaram D, Khincha HP. Application of support vector machines for fault diagnosis in power transmission system. IET Gener Transm Distrib 2008;2:119–30.
Parikh UB, Das B, Maheshwari RP. Combined wavelet-SVM technique for fault zone detection in a series compensated transmission line. IEEE Trans Power Delivery 2008;23:1789–94.
Bhalja B, Maheshwari RP. Wavelet-based fault classification scheme for a transmission line using a support vector machine. Electric Power Compo Syst 2008;36:1017–30.
Parikh UB, Das B, Maheshwari RP. Fault classification technique for series compensated transmission line using support vector machine. Int J Electr Power Energy Syst 2010;32:629–36 [July].
Ekici S. Support vector machines for classification and locating faults on transmission lines. Appl Soft Comput 2012;12:1650–8 [June].
Seethalekshmi K, Singh SN, Srivastava SC. A classification approach using support vector machines to prevent distance relay maloperation under power swing and voltage instability. IEEE Trans Power Delivery 2012;27(3):1124–33 [July].
Jafarian P, Sanaye-Pasand M. High-frequency transients-based protection of multi-terminal transmission lines using the SVM technique. IEEE Trans Power Delivery 2013;28(1):188–96 [January].
Dalei J, Mohanty KB. Fault classification in SEIG system using Hilbert-Huang transform and least square support vector machine. Int J Electr Power Energy Syst March 2016;76:11–22.
Deng X, Yuan R, Xiao Z, Li T, Wang KLL. Fault location in loop distribution network using SVM technology. Int J Electr Power Energy Syst February 2015;65:254–61.
Ye L, You D, Yin X, Wang K, Wu J. An improved fault-location method for distribution system using wavelets and support vector regression. Int J Electr Power Energy Syst February 2014;55:467–72.
B. Rathore, A.G. Shaik, Wavelet-alienation based transmission line protection scheme, IET Gener. Transm. Distrib. 11 (4) (2017) 995–1003.
A.G. Shaik, R.R.V. Pulipaka, A new wavelet based fault detection, classification and location in transmission lines, Int. J. Electr. Power Energy Syst. 64 (2015) 35–40.
A. Yadav, A. Swetapadma, A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach, Int. J. Electr. Power Energy Syst. 69 (2015) 27–33.
M. Mirzaei, B. Vahidi, S.H. Hosseinian, Fault location on a series-compensated three-terminal transmission line using deep neural networks, IET Sci. Meas. Technol. 12 (6) (2018) 746–754.
A. Said, S. Hashima, M. M. Fouda, and M. H. Saad, ‘‘Deep learningbased fault classification and location for underground power cable of nuclear facilities,’’ IEEE Access, vol. 10, pp. 70126–70142, 2022, doi: 10.1109/ACCESS.2022.3187026.
M. H. Saad and A. Said, ‘‘Machine learning-based fault diagnosis for research nuclear reactor medium voltage power cables in fraction Fourier domain,’’ Electr. Eng., pp. 1–18, Sep. 2022, doi: 10.1007/s00202-022- 01649-7.
D. Akmaz, M. S. Mamis, M. Arkan, and M. E. Tagluk, ‘‘Transmission line fault location using traveling wave frequencies and extreme learning machine,’’ Electric Power Syst. Res., vol. 155, pp. 1–7, Feb. 2018, doi: 10.1016/j.epsr.2017.09.019.
M. Al-Gabalawy, A. H. Elmetwaly, R. A. Younis, and A. I. Omar, ‘‘Temperature prediction for electric vehicles of permanent magnet synchronous motor using robust machine learning tools,’’ J. Ambient Intell. Humanized Comput., pp. 1–18, May 2022, doi: 10.1007/ s12652-022-03888-9.
H. V. G. Rao, N. Prabhu, and R. C. Mala, ‘‘Wavelet transform-based protection of transmission line incorporating SSSC with energy storage device,’’ Electr. Eng., vol. 102, no. 3, pp. 1593–1604, Sep. 2020, doi: 10.1007/s00202-020-00978-9.
A. Yadav and A. Swetapadma, ‘‘Enhancing the performance of transmission line directional relaying, fault classification and fault location schemes using fuzzy inference system,’’ IET Gener., Transmiss. Distrib., vol. 9, no. 6, pp. 580–591, Apr. 2015, doi: 10.1049/iet- td.2014.0498.
M. J. Reddy and D. K. Mohanta, ‘‘A wavelet-fuzzy combined approach for classification and location of transmission line faults,’’ Int. J. Electr. Power Energy Syst., vol. 29, no. 9, pp. 669–678, Nov. 2007, doi: 10.1016/j.ijepes.2007.05.001.
T.F. Moraes, L. Lovisolo, L.F.C. Monteiro, Fault location in distribution systems from analysis of the energy of sequence component waveforms, IET Gener. Transm. Distrib. 12 (9) (2018) 1951–1960.
S. Biswal, M. Biswal, O.P. Malik, Hilbert Huang transform based online differential relay algorithm for a shunt-compensated transmission line, IEEE Trans. Power Deliv. 33 (6) (2018) 2803–2811.
B. Chatterjee, S. Debnath, Fuzzy based relaying scheme for transmission line based on unsynchronized voltage measurement, IETE J. Res. (2020) 10.1080/03772063. 2020.1754934.
P. Jena, A.K. Pradhan, An integrated approach for directional relaying of the double-circuit line, IEEE Trans. Power Deliv. 26 (3) (2011) 1783–1792.
B. Chatterjee, S. Debnath, Cross-correlation aided fuzzy based relaying scheme for fault classification in transmission lines, Eng. Sci. Technol. Int. J. 23 (2020) 534–543.
Downloads
Published
How to Cite
Issue
Section
Altmetrics
Downloads
License
Copyright (c) 2023 AiBi Journal of Research, Administration and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.
The journal offers open access under a Creative Commons Attibution License
This work is under license Creative Commons Attribution (CC BY 4.0).
